Things worth avoiding
Some lessons are easier to learn from someone else’s mistakes. These are the most common pitfalls we see — technical, creative, and ethical — with practical ways to steer clear.
Claiming that AI-generated or AI-assisted artwork was created entirely by hand is deceptive, damages trust, and undermines the credibility of both the artist and the broader AI art community.
How to avoid it
Adopt transparent labeling practices. Include AI involvement in your artist statement, exhibition labels, and social media posts. Use emerging standards like the Content Authenticity Initiative (CAI) metadata to embed provenance information directly in your files. Be specific: describe what the AI contributed and what you contributed.
Using AI to deliberately replicate the distinctive visual style of a living artist — especially for commercial purposes — raises serious ethical concerns and growing legal risks.
How to avoid it
Reference art movements and historical periods rather than living individuals. Use descriptive aesthetic terms instead of artist names. If you admire a living artist's approach, study their techniques and develop your own interpretation rather than prompting an AI to copy theirs.
Every AI image generator is built on a foundation of training data — millions of images created by human artists. Ignoring the ethical implications of this foundation undermines the creative community you are part of and exposes you to reputational and legal risk.
How to avoid it
Research the training data provenance of the AI tools you use. Prefer tools that use licensed, consented, or public domain training data when available. Acknowledge the training data dependency in your artist statements. Support initiatives for fair compensation of artists whose work is used in training datasets.
Spamming art platforms with high volumes of low-effort AI-generated content degrades the ecosystem for everyone — artists, audiences, and platforms alike. Quality and curation should always take precedence over quantity.
How to avoid it
Treat AI as a tool for quality, not quantity. Curate ruthlessly — publish only your best work. Respect platform norms and submission guidelines. Tag AI-generated content honestly. Contribute to communities rather than extracting attention from them.
Using AI to generate realistic images of real people without their consent — whether for harassment, fraud, pornography, or deception — is one of the most serious ethical violations in AI art and is increasingly illegal in jurisdictions worldwide.
How to avoid it
Never generate realistic images of identifiable real people without their explicit consent. Avoid training models on individuals' likenesses without permission. If your art involves real people, use abstraction, collage, or clearly non-photorealistic styles that cannot be mistaken for documentation. Stay current with deepfake legislation in your jurisdiction.
AI image generators produce output that can contain errors, biases, unintended content, and artifacts that are invisible at first glance. Publishing AI-generated work without thorough human review risks embarrassment, harm, and the erosion of your credibility as an artist.
How to avoid it
Establish a mandatory review process for all AI-generated content before publication. Check for anatomical accuracy, text artifacts, unintended content, cultural sensitivity, and bias. Use multiple review passes at different zoom levels. Get a second pair of human eyes on work before it goes public.
AI image generators have no understanding of cultural meaning, historical significance, sacred symbolism, or social context. Treating AI output as culturally competent can lead to offensive, appropriative, or harmful representations that damage your reputation and cause real harm to the communities depicted.
How to avoid it
Research the cultural context of any imagery you work with. Consult members of the cultures you depict. Never rely on AI's representation of cultural elements without independent verification. Approach unfamiliar cultural material with humility and a willingness to learn before you create.
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